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Variable refrigerant flow (VRF) and variable air volume (VAV) systems are considered among the best heating, ventilation, and air conditioning systems (HVAC) thanks to their ability to provide cooling and heating in different thermal zones of the same building. As well as their ability to recover the heat rejected from spaces requiring cooling and reuse it to heat another space. Nevertheless, at the same time, these systems are considered one of the most energy-consuming systems in the building. So, it is crucial to well size the system according to the building’s cooling and heating needs and the indoor temperature fluctuations. This study aims to compare these two energy systems by conducting an energy model simulation of a real building under a semi-arid climate for cooling and heating periods. The developed building energy model (BEM) was validated and calibrated using measured and simulated indoor air temperature and energy consumption data. The study aims to evaluate the effect of these HVAC systems on energy consumption and the indoor thermal comfort of the building. The numerical model was based on the Energy Plus simulation engine. The approach used in this paper has allowed us to reach significant quantitative energy saving along with a high level of indoor thermal comfort by using the VRF system compared to the VAV system. The findings prove that the VRF system provides 46.18% of the annual total heating energy savings and 6.14% of the annual cooling and ventilation energy savings compared to the VAV system.
To improve the building’s energy efficiency many parameters should be assessed considering the building envelope, energy loads, occupation, and HVAC systems. Fenestration is among the most important variables impacting residential building indoor temperatures. So, it is crucial to use the most optimal energy-efficient window glazing in buildings to reduce energy consumption and at the same time provide visual daylight comfort and thermal comfort. Many studies have focused on the improvement of building energy efficiency focusing on the building envelope or the heating, ventilation, and cooling systems. But just a few studies have focused on studying the effect of glazing on building energy consumption. Thus, this paper aims to study the influence of different glazing types on the building’s heating and cooling energy consumption. A real case study building located under a semi-arid climate was used. The building energy model has been conducted using the OpenStudio simulation engine. Building indoor temperature was calibrated using ASHRAE’s statistical indices. Then a comparative analysis was conducted using seven different types of windows including single, double, and triple glazing filled with air and argon. Tripleglazed and double-glazed windows with argon space offer 37% and 32% of annual energy savings. It should be stressed that the methodology developed in this paper could be useful for further studies to improve building energy efficiency using optimal window glazing.
The variable refrigerant flow system is one of the best heating, ventilation, and air conditioning systems (HVAC) thanks to its ability to provide thermal comfort inside buildings. But, at the same time, these systems are considered one of the most energy-consuming systems in the building sector. Thus, it is crucial to well size the system according to the building’s cooling and heating needs and the indoor temperature fluctuations. Although many researchers have studied the optimization of the building energy performance considering heating or cooling needs, using air handling units, radiant floor heating, and direct expansion valves, few studies have considered the use of multi-objective optimization using only the thermostat setpoints of VRF systems for both cooling and heating needs. Thus, the main aim of this study is to conduct a sensitivity analysis and a multi-objective optimization strategy for a residential building containing a variable refrigerant flow system, to evaluate the effect of the building performance on energy consumption and improve the building energy efficiency. The numerical model was based on the EnergyPlus, jEPlus, and jEPlus+EA simulation engines. The approach used in this paper has allowed us to reach significant quantitative energy saving by varying the cooling and heating setpoints and scheduling scenarios. It should be stressed that this approach could be applied to several HVAC systems to reduce energy-building consumption.
The contribution of the RoofKIT student team to the SDE 21/22 competition is the extension of an existing café in Wuppertal, Germany, to create new functions and living space for the building with simultaneous energetic upgrading. A demonstration unit is built representing a small cut-out of this extension. The developed energy concept was thoroughly simulated by the student team in seminars using Modelica. The system uses mainly solar energy via PVT collectors as the heat source for a brine-water heat pump (space heating and hot water). Energy storage (thermal and electrical) is installed to decouple generation and consumption. Simulation results confirm that carbon neutrality is achieved for the building operation, consuming and generating around 60 kWh/m2a.
With the need for automatic control based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear behaviour of the components but also certain unknown process dynamics like their internal control logic. At the Institute of Energy Systems Technology in Offenburg we have built a real-life microscale trigeneration plant and present in this paper a rational modelling procedure that satisfies the necessary characteristics for models to be applied in model predictive control for grid-reactive optimal scheduling of this complex energy system. These models are validated against experimental data and the efficacy of the methodology is discussed. Their application in the future for the optimal scheduling problem is also briefly motivated.
The transformation of the building energy sector to a highly efficient, clean, decentralised and intelligent system requires innovative technologies like microscale trigeneration and thermally activated building structures (TABS) to pave the way ahead. The combination of such technologies however presents a scientific and engineering challenge. Scientific challenge in terms of developing optimal thermo-electric load management strategies based on overall energy system analysis and an engineering challenge in terms of implementing these strategies through process planning and control. Initial literature research has pointed out the need for a multiperspective analysis in a real life laboratory environment. To this effect an investigation is proposed wherein an analytical model of a microscale trigeneration system integrated with TABS will be developed and compared with a real life test-rig corresponding to building management systems. Data from the experimental analysis will be used to develop control algorithms using model predictive control for achieving the thermal comfort of occupants in the most energy efficient and grid reactive manner. The scope of this work encompasses adsorption cooling based microscale trigeneration systems and their deployment in residential and light commercial buildings.
Microscale trigeneration systems are highly flexible in their operation and thus offer the technical possibility for peak load shifting in building demand side management. However to harness their potential modern control methods such as model predictive control must be implemented for their optimal scheduling. In literature the need for experimental investigation of microscale trigeneration systems to identify typical characteristics of the components and their interactions has been identified. On a real-life setup control specific information of the components is collected and lessons learnt during commissioning of the equipment is shared. The data is analysed to draw the vital characteristics of the system and it will be used for creating models of the components that can be utilised for optimal control.
This study presents some results from a monitoring project with night ventilation and earthto-air heat exchanger. Both techniques refer to air-based low-energy cooling. As these technologies are limited to specific boundary conditions (e.g. moderate summer climate, low temperatures during night, or low ground temperatures, respectively), water-based low-energy cooling may be preferred in many projects. A comparison of the night-ventilated building with a ground-cooled building shows major differences in both concepts.
The German Weather Service (DWD) releases a heat warning, when the weather forecast provides a warm, humid, sunny, and windless weather condition during the next days. The heat stress is calculated by the so called Klima-Michel model. If the apparent air temperature exceeds ca. 32°C / 38°C, there is a strong / extreme heat stress. The smallest forecast area is each administrative district. As people (and especially the vulnerable population) stay most of the time indoors, the heat health warning system was extended by the prediction of heat stress in typical rooms. Therewith it is feasible to forecast the heat stress using a combination of the outdoor and indoor heat stress. The prediction for the indoor heat stress is based on the same weather forecast like the Heat Health Warning Systems (HHWS).and calculates the heat stress by the PMV-model (predicted mean vote). Based on a sophisticated data analysis and simulation study, realistic but summer-critical living situations were defined and implemented in the building simulation program ESP-r. As the simulation runs especially for extreme weather conditions, a simplified building model cannot be used. Standardized input/output routines and an adaptive handover of start values provide for short run times for each forecast area. Good building designs and urban planning provide effective measures to reduce heat stress in cities. However, we have to also pay attention to the present building stock under climate change and a higher heat-wave risk. The extended German HHWS provide information for the emergency services to support the social assistants during heat waves.